Why should we care about data structures in data science? In this short article, I discussed the building blocks of data in Python and summarized the most important things about Python's native data structures, NumPy, and Pandas.
This learning journal aims to summarize the essence of the Stanford Machine Learning coursework in a way that (hopefully) most people new to AI would understand & appreciate. Additionally, I inserted lots of fun comments & graphs to clarify concepts and/or make them more relatable.
"A journey of a thousand miles begins with a single step." There is a lot to learn on this data science journey, but AI frontrunner, Stanford professor, Andrew Ng's T-shaped learning framework can serve as a guiding light for all who are new to AI.
In 2018 summer, I decided to disrupt my career by leaving my actuarial science comfort zone and take a new role in data science. In the next two years, I will document my data science journey and write learning journals to gather pearls of wisdom in #dataScience, #machineLearning, #AI, and other cool things I learned along the way. I hope my journals will serve as an effective learning & motivation tool for myself and others who are also interested in this career path.